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Biology subjects

Keeling, M. J.

Publications and source records attributed to Keeling, M. J..

6 recordsLinked to original sources

The impacts of exogenous noise on stochastic disease dynamics

Much of the literature and intuition associated with mathematical epidemiology is driven by deterministic models, which are a reasonable assumption when the population size is large. Stochastic models, especially individual based models, are however considered vital when dealing with small population sizes, especially at times of invasion or extinction. The overwhelming majority of these models (both deterministic and stochastic) assume that the underlying parameters are fixed (or follow a regular seasonal pattern). Here, we consider an analytic framework for dealing with randomly varying parameters through the use of stochastic differential equations - thereby capturing the action of external noisy processes such as weather. In particular, we focus on when the transmission rate, {beta}, varies as the solution to a Cox-Ingersoll-Ross Model, such that {beta} is gamma distributed with autocorrelation. We consider the impact of this parameter variation on a stochastic version of the Susceptible-Infected-Recovered model, and for this 'double-stochastic' model show through simulation and analytical results that exogenous noise increases the impact of stochasticity, potentially leading to more early extinctions, wider variations in the number of cases at equilibrium, but that early growth rate can be faster or slower depending on the precise parameters.

systems biology↗

Drivers of Rift Valley fever virus persistence and the impact of control measures in a spatially heterogeneous landscape: the case of the Comoros archipelago, 2004-2015

Rift Valley fever (RVF) is one of the many zoonotic arboviral haemorrhagic fevers present in Africa. The ability of the pathogen to persist in multiple geographically distinct regions has raised concerns about its potential for spread to and persistence within currently disease-free areas. However, the mechanisms for which RVF virus persistence occurs at both local and broader geographical scales have yet to be fully understood and rigorously quantified. Here, we developed a mathematical metapopulation model describing RVF virus transmission in livestock across the four islands of the Comoros archipelago and fitted this model in a Bayesian framework to surveillance data conducted in livestock across those islands between 2004 and 2015. In doing so, we estimated the importance of island-specific environmental factors and animal movements between those islands on the persistence of RVF virus in the archipelago, and we further tested the impact of different control scenarios on reducing disease burden. We demonstrated that the archipelago network was able to sustain viral transmission over 10 years after assuming only one introduction event during early 2007. Movement restrictions were only useful to control the disease in Anjouan and Mayotte, as Grande Comore and Moheli were able to self-sustain RVF viral persistence, probably due to local environmental conditions that are more favourable for vectors. We also evidenced that repeated outbreaks during 2004-2020 may have gone under-detected by local surveillance in Grande Comore and Moheli. Strengthened longterm and coordinated surveillance would enable the detection of viral re-emergence and evaluation of different relevant vaccination programmes.

ecology↗

Feedback Between Coevolution and Epidemiology Can Help or Hinder the Maintenance of Genetic Variation in Host-Parasite Models

Understanding if and when coevolution helps maintains genetic variation in hosts of a directly-transmissible pathogen is fundamental to quantifying the prevalence and impact of coevolution on disease epidemiology. Here, we extend our previous work on the maintenance of genetic variation in a classic matching-alleles coevolutionary model by exploring the effects of ecological and epidemiological feedbacks, where both allele frequencies and population sizes are allowed to vary over time. In general, we find that coevolution rarely maintains more host genetic variation than expected under neutral genetic drift alone. When and if coevolution maintains or depletes genetic variation relative to neutral drift is determined, predominantly, by two factors: the deterministic stability of the Red Queen allele frequency cycles and the frequency at which pathogen fixation occurs, as this results in directional selection and the depletion of genetic variation in the host. Compared to purely coevolutionary models with constant host and pathogen population sizes, ecological and epidemiological feedbacks stabilize Red Queen cycles deterministically, but population fluctuations in the pathogen increase the rate of pathogen fixation, especially in epidemiological models. Taken together our results illustrate the importance of considering the ecological and epidemiological context in which coevolution occurs when examining the impact of Red Queen cycles on genetic variation.

evolutionary biology↗

Coevolution does not slow the rate of loss of heterozygosity in a stochastic host-parasite model with constant population size

Coevolutionary negative frequency dependent selection has been hypothesized to maintain genetic variation in host and parasites. Despite the extensive literature pertaining to host-parasite coevolution, the effect of matching-alleles (MAM) coevolution on the maintenance of genetic variation has not been explicitly modelled in a finite population. The dynamics of the MAM in an infinite population, in fact, suggests that genetic variation in these coevolving populations behaves neutrally. We find that while this is largely true in finite populations two additional phenomena arise. The first of these effects is that of coevolutionary natural selection on stochastic perturbations in host and pathogen allele frequencies. While this may increase or decrease genetic variation, depending on the parameter conditions, the net effect is small relative to that of the second phenomena. Following fixation in the pathogen, the MAM becomes one of directional selection, which in turn rapidly erodes genetic variation in the host. Hence, rather than maintain it, we find that, on average, matching-alleles coevolution depletes genetic variation.

evolutionary biology↗

Seasonal influenza: Modelling approaches to capture immunity propagation

Seasonal influenza poses serious problems for global public health, being a significant contributor to morbidity and mortality. In England, there has been a long-standing national vaccination programme, with vaccination of at-risk groups and children offering partial protection against infection. Transmission models have been a fundamental component of analysis, informing the efficient use of limited resources. However, these models generally treat each season and each strain circulating within that season in isolation. Here, we amalgamate multiple data sources to calibrate a susceptible-latent-infected-recovered type transmission model for seasonal influenza, incorporating the four main strains and mechanisms linking prior season epidemiological out-comes to immunity at the beginning of the following season. Data pertaining to nine influenza seasons, starting with the 2009/10 season, informed our estimates for epidemiological processes, virological sample positivity, vaccine uptake and efficacy attributes, and general practitioner influenza-like-illness consultations as reported by the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC). We performed parameter inference via approximate Bayesian computation to assess strain transmissibility, dependence of present season influenza immunity on prior protection, and variability in the influenza case ascertainment across seasons. This produced reasonable agreement between model and data on the annual strain composition. Parameter fits indicated that the propagation of immunity from one season to the next is weaker if vaccine derived, compared to natural immunity from infection. Projecting the dynamics forward in time suggests that while historic immunity plays an important role in determining annual strain composition, the variability in vaccine efficacy hampers our ability to make long-term predictions.

epidemiology↗

Reducing RSV hospitalisation in a lower-income country by vaccinating mothers-to-be and their households

Respiratory syncytial virus is the leading cause of lower respiratory tract infection among infants. RSV is a priority for vaccine development. In this study, we investigate the potential effectiveness of a two-vaccine strategy aimed at mothers-to-be, thereby boosting maternally acquired antibodies of infants, and their household cohabitants, further cocooning infants against infection. We use a dynamic RSV transmission model which captures transmission both within households and communities, adapted to the changing demographics and RSV seasonality of a low-income country. Model parameters were inferred from past RSV hospitalisations, and forecasts made over a 10-year horizon. We find that a 50% reduction in RSV hospitalisations is possible if the maternal vaccine effectiveness can achieve 75 days of additional protection for newborns combined with a 75% coverage of their birth household co-inhabitants ([~]7.5% population coverage).

epidemiology↗